Extreme-Ultraviolet-Initated High-Order Harmonic Generation: Driving Inner-Valence Electrons Using Below-Threshold-Energy Extreme-Ultraviolet Light

We propose a novel scheme for resolving the contribution of inner- and outer-valence electrons in XUV-initiated high-harmonic generation in neon. By probing the atom with a low energy (below the 2s ionisation threshold) ultrashort XUV pulse, the 2p electron is steered away from the core, while the 2s electron is enabled to describe recollision trajectories. By selectively suppressing the 2p recollision trajectories we can resolve the contribution of the 2s electron to the high-harmonic spectrum. We apply the classical trajectory model to account for the contribution of the 2s electron, which allows for an intuitive understanding of the process.

Inter-Laboratory Evaluation of a Next-Generation Sequencing Panel for Acute Myeloid Leukemia

INTRODUCTION: Acute myeloid leukemia (AML) is a heterogeneous clonal disorder often associated with dismal overall survival. The clinical diversity of AML is reflected in the range of recurrent somatic mutations in several genes, many of which have a prognostic and therapeutic value. Targeted next-generation sequencing (NGS) of these genes has the potential for translation into clinical practice. In order to assess this potential, an inter-laboratory evaluation of a commercially available AML gene panel across three diagnostic centres in the UK and Ireland was performed.

METHODS: DNA from six AML patient samples was distributed to each centre and processed using a standardised workflow, including a common sequencing platform, sequencing chips and bioinformatics pipeline. A duplicate sample in each centre was run to assess inter- and intra-laboratory performance.

RESULTS: An average sample read depth of 2725X (range 629-5600) was achieved using six samples per chip, with some variability observed in the depth of coverage generated for individual samples and between centres. A total of 16 somatic mutations were detected in the six AML samples, with a mean of 2.7 mutations per sample (range 1-4) representing nine genes on the panel. 15/16 mutations were identified by all three centres. Allelic frequencies of the mutations ranged from 5.6 to 53.3 % (median 44.4 %), with a high level of concordance of these frequencies between centres, for mutations detected.

CONCLUSION: In this inter-laboratory comparison, a high concordance, reproducibility and robustness was demonstrated using a commercially available NGS AML gene panel and platform.

Control Strategues for Automatic Generation Control over MTDC Grid

Increasingly in power systems, there is a trend towards the sharing of reserves and integration of markets over wide areas in order to enable increased penetration of renewable sources in interconnected power systems. In this paper, a number of simple PI and gain based Model Predictive Control algorithms are proposed for Automatic Generation Control in AC areas connected to Multi-Terminal Direct Current grids. The paper discusses how this approach improves the sharing of secondary reserves and could assist in achieving EU energy targets for 2030 and beyond.

Application of Volterra Equations to Solve Unit Commitment Problem of Optimised Energy Storage and Generation

Development of reliable methods for optimised energy storage and generation is one of the most imminent challenges in modern power systems. In this paper an adaptive approach to load leveling problem using novel dynamic models based on the Volterra integral equations of the first kind with piecewise continuous kernels. These integral equations efficiently solve such inverse problem taking into account both the time dependent efficiencies and the availability of generation/storage of each energy storage technology. In this analysis a direct numerical method is employed to find the least-cost dispatch of available storages. The proposed collocation type numerical method has second order accuracy and enjoys self-regularization properties, which is associated with confidence levels of system demand. This adaptive approach is suitable for energy storage optimisation in real time. The efficiency of the proposed methodology is demonstrated on the Single Electricity Market of Republic of Ireland and Northern Ireland.

Statistical Analysis of Wind Power Generation in Europe

Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.

The mental health and wellbeing of first generation migrants: a systematic-narrative review of reviews

Background
First generation migrants are reportedly at higher risk of mental ill-health compared to the settled population. This paper systematically reviews and synthesizes all reviews on the mental health of first generation migrants in order to appraise the risk factors for, and explain differences in, the mental health of this population.
Methods
Scientific databases were searched for systematic reviews (inception-November 2015) which provided quantitative data on the mental ill-health of first generation migrants and associated risk factors. Two reviewers screened titles, abstracts and full text papers for their suitability against pre-specified criteria, methodological quality was assessed.
Results
One thousand eight hundred twenty articles were identified, eight met inclusion criteria, which were all moderate or low quality. Depression was mostly higher in first generation migrants in general, and in refugees/asylum seekers when analysed separately. However, for both groups there was wide variation in prevalence rates, from 5 to 44 % compared with prevalence rates of 8–12 % in the general population. Post-Traumatic Stress Disorder prevalence was higher for both first generation migrants in general and for refugees/asylum seekers compared with the settled majority. Post-Traumatic Stress Disorder prevalence in first generation migrants in general and refugees/ asylum seekers ranged from 9 to 36 % compared with reported prevalence rates of 1–2 % in the general population. Few studies presented anxiety prevalence rates in first generation migrants and there was wide variation in those that did. Prevalence ranged from 4 to 40 % compared with reported prevalence of 5 % in the general population. Two reviews assessed the psychotic disorder risk, reporting this was two to three times more likely in adult first generation migrants. However, one review on the risk of schizophrenia in refugees reported similar prevalence rates (2 %) to estimates of prevalence among the settled majority (3 %). Risk factors for mental ill-health included low Gross National Product in the host country, downward social mobility, country of origin, and host country.
Conclusion
First generation migrants may be at increased risk of mental illness and public health policy must account for this and influencing factors. High quality research in the area is urgently needed as is the use of culturally specific validated measurement tools for assessing migrant mental health.